Addiction is a mental disorder within the mental health spectrum, and it matters
Bibliographic record
Abstract
Substance use disorders and addictions are mental disorders deeply interconnected with other psychiatric conditions - and this connection is of fundamental importance. Although addictions are formally recognized as mental health disorders, they are often not addressed as such in research or clinical practice. Psychiatric research, clinical care, and treatment development remain largely organized along traditional diagnostic boundaries. While diagnostic classifications provide structure and clinical utility, it is increasingly evident that psychiatric diagnoses are neither fully separable nor independent entities. Despite extensive discussion on comorbidity, addictions are frequently excluded from broader conceptualizations of the intertwined nature of mental disorders. Yet, they share substantial commonalities with other psychiatric conditions across clinical presentation, psychopathology, genetic vulnerability, neurobiological mechanisms, socioenvironmental risk factors, and treatment strategies. Maintaining a conceptual divide between addictions and other psychiatric disorders reinforces diagnostic "tunnel vision," constraining our understanding of neuropsychopathology and contributing to persistent gaps in care and treatment accessibility. This narrative review examines the overlapping risk factors, clinical features, and therapeutic approaches that link addictions with other mental disorders. We argue that advancing psychiatric research and nosology requires a deliberate acknowledgement of these transdiagnostic overlaps and shared mechanisms. The challenge is particularly evident in the understanding and treatment of dual disorders. Progress will depend on integrative, collaborative frameworks that bridge scientific and clinical perspectives and foster dynamic feedback between empirical research and clinical practice. Recognizing mental disorders as interdependent systems may offer a more coherent and effective foundation for understanding and treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".